Abstract
Nucleoside analogs have been widely used as antiviral, antitumor, and antiparasitic agents due to their ability to inhibit nucleic acid synthesis. Adenosine, cytidine, guanosine, thymidine and uridine analogs such as didanosine, vidarabine, remdesivir, gemcitabine, lamivudine, acyclovir, abacavir, zidovusine, stavudine, and idoxuridine showed remarkable anticancer and antiviral activities. In our previously published articles, our main intention was to develop newer generation nucleoside analogs with acylation-induced modification of the hydroxyl group and showcase their biological potencies. In the process of developing nucleoside analogs, in silico studies play an important role and provide a scientific background for biological data. Molecular interactions between drugs and receptors followed by assessment of their stability in physiological environments, help to optimize the drug development process and minimize the burden of unwanted synthesis. Computational approaches, such as DFT, FMO, MEP, ADMET prediction, PASS prediction, POM analysis, molecular docking, and molecular dynamics simulation, are the most popular tools to culminate all preclinical study data and deliver a molecule with maximum bioactivity and minimum toxicity. Although clinical drug trials are crucial for providing dosage recommendations, they can only indirectly provide mechanistic information through researchers for pathological, physiological, and pharmacological determinants. As a result, in silico approaches are increasingly used in drug discovery and development to provide mechanistic information of clinical value. This article portrays the current status of these methods and highlights some remarkable contributions to the development of nucleoside analogs with optimized bioactivity.
Graphical Abstract
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